patent-landscape

name	patent-landscape
description	Use when analyzing biotech patent landscapes, identifying white spaces in pharmaceutical IP, tracking competitor patents, or assessing freedom to operate for drug development. Provides comprehensive patent analysis and strategic insights for life sciences innovation.
allowed-tools	Read Write Bash Edit
license	MIT
metadata	{"skill-author":"AIPOCH","version":"1.0"}

Biotech Patent Landscape Analyzer

Analyze biotech and pharmaceutical patent landscapes to identify opportunities, assess competition, and guide R&D strategy.

Quick Start

from scripts.patent_landscape import PatentLandscapeAnalyzer

analyzer = PatentLandscapeAnalyzer()

# Analyze therapeutic area
landscape = analyzer.analyze(
    therapeutic_area="CAR-T cell therapy",
    date_range="2020-2024",
    assignees=["Novartis", "Kite Pharma", "Juno Therapeutics"]
)

Core Capabilities

1. Patent Search & Analysis

results = analyzer.search_patents(
    keywords=["CRISPR", "gene editing", "therapeutic"],
    classification="C12N15/113",  # IPC class
    jurisdictions=["US", "EP", "WO"]
)

Search Strategies:

• Keyword-based: Technical terms + synonyms
• Classification-based: IPC/CPC codes
• Citation-based: Forward/backward citations
• Assignee-based: Company portfolios

2. White Space Analysis

opportunities = analyzer.identify_white_spaces(
    technology="Antibody-drug conjugates",
    target_diseases=["breast cancer", "lung cancer"],
    existing_claims=landscape
)

White Space Opportunities:

• Underserved disease indications
• Novel combination therapies
• Alternative delivery mechanisms
• Geographical gaps (emerging markets)

3. Competitor Intelligence

competitors = analyzer.analyze_competitors(
    companies=["Pfizer", "Moderna", "BioNTech"],
    focus_area="mRNA vaccines"
)

Competitor Metrics:

Metric	Description
Portfolio size	Total active patents
Filing velocity	Recent filing trends
Geographic coverage	Jurisdiction strategy
Technology focus	Core vs. peripheral areas
Partnership patterns	Collaboration trends

4. Freedom to Operate (FTO) Assessment

fto = analyzer.assess_fto(
    product_concept="Bispecific antibody targeting PD-1 and CTLA-4",
    jurisdictions=["US", "EU", "Japan"]
)

FTO Analysis Steps:

1. Identify relevant patent claims
2. Map claims to product features
3. Assess validity of blocking patents
4. Design around options
5. Licensing recommendations

CLI Usage

# Generate patent landscape report
python scripts/patent_landscape.py \
  --query "immuno-oncology checkpoint inhibitors" \
  --output landscape_report.pdf \
  --format comprehensive

# Quick FTO check
python scripts/patent_landscape.py \
  --fto "product_description.txt" \
  --jurisdictions US EP JP

Data Sources

• USPTO (United States)
• EPO (Europe)
• WIPO (Global)
• JPO (Japan)
• CNIPA (China)

References

• references/ipc-classifications.md - IPC/CPC codes for biotech
• references/patent-search-strategies.md - Advanced search techniques
• examples/landscape-reports/ - Sample reports

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Skill ID: 204 | Version: 1.0 | License: MIT